Stochastic particle-resolved aerosol models provide a new way of simulating atmospheric aerosol. While traditional aerosol models are distribution-based, particle-resolved models track individual particles as they undergo chemical and physical transformations in the atmosphere. This is computationally expensive but has the advantage that the evolution of the per-particle composition can be simulated without any approximating assumptions. Hence aerosol impacts that depend on per-particle composition, e.g. optical properties and cloud condensation activity, can be represented in detail. As such, particle-resolved models are invaluable in the model hierarchy. They serve as a benchmark for more approximate models, to derive parameters that are used in more approximate models, as well as to perform detailed process studies on the particle scale.
In this talk I will present the underlying theory of particle-resolved models and our recent model development of the stochastic particle-resolved model PartMC-MOSAIC. I will illustrate the usefulness of this approach by focusing on the aging process of black-carbon-containing particles. The adequate representation of these aging processes in models is a key challenge in determining the climate-relevant properties of black carbon, a short-lived climate forcer. Using PartMC-MOSAIC we are able to quantify the individual processes that contribute to the aging of the aerosol distribution and demonstrate the effect of aerosol mixing state on aging time scales, optical properties, and CCN activation properties.